Utilizing NDVI and remote sensing data to identify spatial variability in plant stress as influenced by management

摘要: Understanding plant stress and its spatial distribution has been a goal of both crop physiologists producers. Recognizing variability in growth early can aid identifying yield-limiting factors such as soils, nutrient availability, and/or environmental limitations. Active sensors have used to gather reflectance data from canopies calculate NDVI (Normalized Difference Vegetative Index). associated with percent ground cover, LAI, biomass accumulation, nitrogen use efficiency. This study contends that be characterize is correlated grain yield. values were measured bi-weekly through the growing seasons 2010 2011in corn (Zea mays L.) grown at location soil topographic variability. Grain yield was collected following each season. Management practices characteristics site plot order identify contributing variations values. Two cropping rotations used, continuous corn, soybean small grain/soybean double crop. Results showed differences different landscape positions could identified NDVI. The strength this relationship greatest eight weeks after planting. A also established between measurements production when taken accumulation 800 900 degree days. demonstrated success presents opportunity technology characterizing potential making managerial decisions across landscape.